Demonstrates improved estimation of solar irradiance in various climates, suggesting enhanced data reliability for energy modeling.
High temporal-resolution solar irradiance data are essential for a wide range of energy and climate applications. However, most climate models and reanalysis datasets are only available at hourly resolution. ETHOS.TISED is an open-source Python package which facilitates the temporal downscaling of global horizontal irradiance from hourly to minute-scale resolution, using daily variability indicators for all climates and locations. The synthetically generated minute-scale resolution data show close agreement with measured observations as demonstrated by the normalized root mean squared error and the Kolmogorov-Smirnov integral test, which quantify the point-to-point and distributional divergence between measured and synthesized time series, respectively. By enabling the reproducible generation of high-frequency irradiance time series, the software improves the robustness and reliability of research and applied studies in energy system modeling.
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Omoyele et al. (2026) studied this question.
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